In this paper, the intraframe correlation properties of Line Spectrum Pair (LSP) are used to develop an efficient encoding algorithm using the Karhunen-Loeve (KL) transformation. An important nonuniform statistical characteristics of LSP frequencies are investigated. Based upon this nonuniform property the neural network based techniques for generating the transform vectors via system training are studied. Using Principal Component Analysis (PCA) network to decorrelate LSP coefficients, we show that these new approaches lead to as good or better distortion as compared to other methods for speech analysis-synthesis.
|Number of pages||4|
|Publication status||Published - 1 Jan 1997|
|Event||Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 5) - Munich, Ger|
Duration: 21 Apr 1997 → 24 Apr 1997